
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "104"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 84 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 80 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.669755	-0.467904	8.042293	-0.472387	0.894857	-0.255520	5.472066	-0.693073	0.8145	0.8148	0.2358	12.504330	12.607112
2459593	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.444214	-0.088791	8.765010	-0.615816	0.078809	-1.035409	2.764437	-0.896978	0.7577	0.7500	0.2470	5.489890	5.339013
2459592	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	0.254005	-0.992085	0.442413	1.575799	-0.326962	0.142641	-1.923749	-0.168209	0.0306	0.0279	0.0005	nan	nan
2459591	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.468501	-0.081534	10.850893	0.255622	0.083010	-0.133604	-0.488204	-0.930897	0.6910	0.7028	0.3621	4.268058	4.448180
2459590	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.094975	0.291116	10.776500	-0.375406	0.167171	1.901191	0.058197	-0.935806	0.6914	0.7013	0.3577	5.849115	5.916475
2459589	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.543788	-0.401365	9.601300	-1.042338	1.118744	-1.082255	4.156268	-0.906123	0.7379	0.7303	0.2760	5.751909	5.655925
2459588	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.374424	-1.236711	11.601281	-0.473816	0.275465	0.027883	2.542408	-0.368308	0.8010	0.7850	0.2093	9.941707	8.497025
2459587	digital_ok	100.00%	-	-	-	100.00%	0.00%	-1.033658	0.319817	15.602793	1.685175	2.439788	-0.668747	2.301429	-0.003642	nan	nan	nan	36.612657	27.282717
2459586	digital_ok	0.00%	0.00%	0.00%	0.00%	11.89%	5.95%	-0.482707	-0.560409	-0.471373	-0.719844	-0.117885	-0.540463	0.101072	-0.767513	0.6833	0.6909	0.3529	1.525247	1.521143
2459585	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.561760	0.282543	0.112888	-0.934261	-0.634115	0.728157	-0.686977	-0.327963	0.0305	0.0305	0.0008	0.000000	0.000000
2459584	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	17.698622	17.672143	1.391849	1.336286	2.984365	3.815056	-0.578123	-0.836472	0.6934	0.7016	0.3728	0.000000	0.000000
2459583	digital_ok	0.00%	0.00%	0.00%	0.00%	80.65%	19.35%	-0.958218	0.070076	0.122207	-0.853857	-0.767092	0.503463	-0.430110	-0.709561	0.6932	0.6992	0.3750	0.000000	0.000000
2459582	digital_ok	0.00%	0.00%	0.00%	0.00%	45.95%	0.00%	-0.884281	-0.002806	-0.003515	-0.732165	-0.925309	-0.085828	-0.520857	-0.854471	0.6948	0.7014	0.3785	1.290015	1.257273
2459581	digital_ok	0.00%	0.00%	0.00%	0.00%	19.46%	0.00%	-1.190598	0.134235	0.668317	-0.911940	-0.934922	-0.112750	0.487471	-0.827086	0.7047	0.7091	0.3715	1.660320	1.609926
2459580	digital_ok	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.925034	0.108720	0.197461	-0.816893	-0.130824	0.384984	3.479779	-0.710821	0.6956	0.7030	0.3724	0.000000	0.000000
2459579	digital_ok	0.00%	0.00%	0.00%	0.00%	3.76%	0.00%	-0.776845	-0.062034	0.536038	-0.742537	1.657250	-0.150210	0.675165	-0.804767	0.6938	0.7021	0.3748	1.449061	1.405457
2459578	digital_ok	100.00%	100.00%	100.00%	0.00%	-	-	-0.472853	-0.558412	0.363269	1.069400	5.157202	0.007977	1.500177	-0.814812	0.0288	0.0299	0.0008	nan	nan
2459577	digital_ok	0.00%	0.00%	0.00%	0.00%	3.78%	0.00%	-1.170842	-0.107690	0.451194	-0.873284	-0.489686	-0.177702	-0.173982	-0.861828	0.6966	0.7038	0.3728	1.513369	1.490615
2459576	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.807161	-0.325632	0.976472	-0.633189	1.233880	-0.938348	5.406819	-0.730762	0.7160	0.7244	0.3729	5.075559	4.833782
2459575	digital_ok	0.00%	0.00%	0.00%	0.00%	5.38%	0.00%	-1.223584	-0.429914	1.030906	-0.514990	0.281135	-0.600780	1.668760	-0.554669	0.7757	0.7757	0.3140	1.506909	1.519419
2459574	digital_ok	0.00%	0.00%	0.00%	0.00%	3.78%	0.00%	-0.970897	-0.291877	0.392364	-0.694413	-0.370090	-1.374230	-0.597733	1.376145	0.7115	0.7193	0.3722	1.659971	1.640285
2459573	digital_ok	0.00%	0.00%	0.00%	0.00%	3.78%	0.00%	-0.672043	-0.244372	0.407020	-0.874187	-1.191961	0.569896	-0.198975	-0.181663	0.7159	0.7229	0.3671	1.508736	1.560317
2459572	digital_ok	0.00%	0.00%	0.00%	0.00%	27.57%	0.00%	-0.905823	-0.574207	0.321093	-0.676949	-0.783610	-0.506776	0.263795	-0.184952	0.7179	0.7235	0.3700	1.449140	1.393800
2459571	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	-0.958464	-0.617350	0.609508	0.808976	-0.879900	-1.315005	-1.054982	-0.960929	0.0379	0.0294	0.0008	nan	nan
2459570	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459569	digital_ok	0.00%	0.00%	0.00%	0.00%	4.32%	0.00%	-0.713999	-0.624655	0.371899	-0.877468	-0.419507	-0.969671	0.310854	-1.012526	0.7896	0.7903	0.2224	2.075861	1.893933
2459566	digital_ok	0.00%	0.00%	0.00%	0.00%	4.32%	0.00%	-1.009797	-0.431998	-0.240303	-0.841534	-0.787314	-0.464576	-0.387836	-0.786572	0.7072	0.7132	0.3841	1.476021	1.455702
2459565	digital_ok	100.00%	-	-	-	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459564	digital_ok	0.00%	0.00%	0.00%	0.00%	6.94%	0.00%	-1.716381	-1.195082	0.613288	-0.327186	-0.543476	-0.749150	0.075909	-0.138736	0.7285	0.7276	0.3806	1.577810	1.465529
2459563	digital_ok	0.00%	0.00%	0.00%	0.00%	5.38%	0.00%	-0.816619	-0.322548	-0.221485	-0.793244	0.297370	1.387355	-0.210238	-0.784682	0.7187	0.7226	0.3797	1.729763	1.628788
2459562	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-1.576121	-1.161769	0.309935	-0.104840	0.027534	-0.061928	0.256983	-0.031061	0.7230	0.7296	0.3754	1.605154	1.543258
2459561	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-1.614527	-1.016108	-0.180079	-0.432527	-0.593602	-0.656207	0.010162	-0.575442	0.7236	0.7313	0.3727	1.526349	1.548047
2459560	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-1.308023	-0.963716	0.093004	-0.385710	-0.191174	-0.507068	0.089630	-0.498364	0.7161	0.7233	0.3846	1.559993	1.518562
2459559	digital_ok	0.00%	0.00%	0.00%	0.00%	5.91%	0.00%	-1.684765	-0.990214	0.145360	-0.331860	-0.682667	-0.863178	0.212446	-0.361028	0.7209	0.7254	0.3708	1.494224	1.445922
2459558	digital_ok	0.00%	0.00%	0.00%	0.00%	5.38%	0.00%	-0.792359	-0.240903	-0.680524	-0.425975	-0.271301	0.208800	-0.157032	-0.772050	0.7246	0.7253	0.3780	1.565813	1.491855
2459557	digital_ok	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0296	0.0284	0.0008	nan	nan
2459556	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-0.615353	0.047984	-0.830183	-0.619657	-0.551132	-0.287934	-0.377276	-1.173779	0.7237	0.7259	0.3738	1.580737	1.513812
2459554	digital_ok	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.7241	0.7274	0.3850	nan	nan
2459553	digital_ok	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.7237	0.7260	0.3823	nan	nan
2459552	digital_ok	100.00%	3.78%	0.00%	0.00%	100.00%	0.00%	0.668585	2.094732	-0.145779	-0.514975	48.594885	10.217468	18.004664	-0.369921	0.7063	0.7265	0.3829	7.654706	8.614780
2459551	digital_ok	0.00%	0.00%	0.00%	0.00%	5.38%	0.00%	-1.444864	-0.998617	-0.006471	-0.483061	-0.701925	-0.705966	0.022203	-0.227429	0.7256	0.7277	0.3720	1.501630	1.437620
2459550	digital_ok	-	96.71%	96.71%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0456	0.0451	0.0004	nan	nan
2459549	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-0.783280	-0.125179	-0.720497	-0.757268	-0.969886	-0.555657	-0.414192	-0.825896	0.7243	0.7286	0.3817	1.576607	1.553400
2459542	digital_ok	0.00%	0.00%	0.00%	0.00%	22.32%	0.00%	-0.155213	-0.297218	-0.511551	0.454939	-0.381491	-0.581530	-0.191119	-0.600831	0.7715	0.7756	0.3331	1.681479	1.508975
2459541	digital_ok	0.00%	1.34%	1.79%	0.00%	21.88%	0.00%	-0.012914	-0.314115	-0.938688	-0.447839	-0.814592	-1.075398	-0.022678	-0.611637	0.7661	0.7591	0.3145	1.487675	1.465798
2459540	digital_ok	0.00%	0.00%	0.00%	0.00%	21.88%	0.00%	-1.554299	-0.777233	-0.422042	-0.690963	-0.128041	1.289872	-0.381269	-0.701705	0.7712	0.7693	0.3253	1.506093	1.432946
2459536	digital_ok	0.00%	0.00%	0.00%	0.00%	5.93%	0.00%	-0.981474	-0.412683	-0.173190	-0.638258	-0.446138	-0.962546	-0.129205	-0.014831	0.7545	0.7512	0.3958	1.607430	1.450189
2459535	digital_ok	0.00%	0.00%	0.00%	0.00%	21.43%	0.00%	-1.171261	-0.810324	-0.228493	-0.773195	0.114013	1.402293	-0.253508	1.707935	0.7971	0.7844	0.3339	1.555816	1.471629
2459534	digital_ok	0.00%	0.00%	0.00%	0.00%	20.98%	0.00%	-1.351378	-0.944097	-0.272231	-0.830110	0.868514	1.861793	-0.038351	-0.598852	0.7852	0.7738	0.3413	1.553562	1.531103
2459533	digital_ok	0.00%	0.00%	0.00%	0.00%	4.89%	0.00%	-0.521102	-0.431981	-0.826082	0.026124	-0.711614	0.562565	-0.132373	-0.842417	0.7380	0.7429	0.3830	1.522739	1.477759
2459532	digital_ok	0.00%	0.00%	0.00%	0.00%	5.00%	0.00%	-0.314914	-0.211647	-0.900736	-0.196610	-0.577393	0.012140	-0.427519	-0.438247	0.7421	0.7403	0.3782	1.586520	1.472517
2459530	digital_ok	0.00%	0.00%	0.00%	0.00%	4.73%	0.00%	-1.503203	-1.242551	-0.175910	-0.544785	-0.404332	-0.506448	0.056520	-0.272309	0.7576	0.7527	0.3811	1.503302	1.456626
2459527	digital_ok	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	digital_ok	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.961074	-0.405866	-0.877027	0.393590	-0.204854	-1.312805	-0.545479	-0.731149	0.9202	0.9475	0.2712	0.000000	0.000000
2459523	digital_ok	0.00%	-	-	-	12.24%	0.00%	-1.047274	-0.314150	-0.938400	0.113977	0.096840	-0.824055	-0.437935	-1.008479	nan	nan	nan	2.290524	2.097437
2459522	digital_ok	0.00%	0.00%	0.00%	0.00%	0.00%	0.00%	-0.520277	-0.504599	-1.051275	-0.085797	-0.719606	-0.654632	-0.142428	-0.912259	0.7166	0.7329	0.3230	1.956267	1.837270
2459513	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	-0.834885	-0.458960	0.652230	0.632250	-1.090527	-0.393278	-0.377462	-0.662908	0.0511	0.0331	0.0021	nan	nan
2459508	digital_ok	0.00%	0.00%	0.00%	0.00%	81.58%	0.00%	-1.075376	0.012753	-0.928397	-0.206030	-0.225103	-0.292678	-1.312753	-0.878170	0.9275	0.9593	0.1530	0.000000	0.000000
2459505	digital_ok	0.00%	0.00%	0.00%	0.00%	0.00%	0.00%	-0.471894	-0.370274	-0.691696	-0.851332	-0.242710	-0.524700	-0.476307	-0.169252	0.8908	0.8782	0.1815	5.105972	4.191054
2459503	digital_ok	0.00%	0.00%	0.00%	0.00%	89.47%	0.00%	-0.988094	-0.304663	-0.849673	-0.264812	-0.575674	-1.183647	0.238620	-0.525386	0.8923	0.8884	0.4142	0.000000	0.000000
2459501	digital_ok	0.00%	0.00%	0.00%	0.00%	76.74%	0.00%	-0.503764	0.512487	-0.231818	0.516511	-0.232728	0.281771	-0.283520	-0.845187	0.8973	0.9246	0.3587	0.000000	0.000000
2459500	digital_ok	0.00%	0.00%	0.00%	0.00%	94.74%	0.00%	-0.720505	0.926308	-0.334811	0.718994	-0.681859	-0.084992	-0.790481	-0.647925	0.9079	0.9230	0.3509	0.000000	0.000000
2459499	digital_ok	0.00%	0.00%	0.00%	0.00%	97.37%	0.00%	-1.277195	0.896788	-0.674438	0.604731	-0.856135	-0.445451	-0.584615	-0.572074	0.9024	0.9503	0.1622	0.000000	0.000000
2459498	digital_ok	0.00%	0.00%	0.00%	0.00%	94.74%	0.00%	-0.833546	0.515355	-0.663871	0.339331	-0.775213	-0.687224	-0.034824	-0.252821	0.9164	0.9261	0.3760	0.000000	0.000000
2459497	digital_ok	0.00%	0.00%	0.00%	0.00%	97.37%	0.00%	-0.695197	2.833155	-0.673616	1.243434	-1.102731	-0.315088	-0.669826	1.568949	0.9239	0.9409	0.3199	0.000000	0.000000
2459496	digital_ok	0.00%	0.00%	0.00%	0.00%	94.74%	0.00%	-1.171732	0.222714	-0.784480	0.212799	-1.253635	-1.370239	0.322923	-0.681975	0.8983	0.9098	0.3562	0.000000	0.000000
2459495	digital_ok	0.00%	0.00%	0.00%	0.00%	94.74%	0.00%	-1.107500	0.217610	-0.806936	0.316186	-0.949853	-0.916296	0.256762	-0.108860	0.8949	0.9055	0.3966	0.000000	0.000000
2459494	digital_ok	0.00%	0.00%	0.00%	0.00%	94.74%	0.00%	-0.834720	1.187578	-0.535523	0.764536	-1.191640	-0.787317	-0.442696	-1.148291	0.8933	0.9013	0.4024	0.000000	0.000000
2459492	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.132164	1.226393	-1.294680	0.382698	0.727308	3.208103	16.749921	23.321395	0.7613	0.8084	0.3225	0.000000	0.000000
2459491	digital_ok	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.360639	0.942705	-1.002449	-0.578905	0.218789	-1.322395	-0.739123	-0.941875	0.8004	0.8236	0.2629	0.000000	0.000000
2459490	digital_ok	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.577947	0.866934	-0.727902	-0.676080	0.906620	-0.508509	0.036256	-0.674883	0.7589	0.8089	0.3569	0.000000	0.000000
2459489	digital_ok	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.445062	0.641733	-1.225697	-0.494089	1.398729	-0.315156	-0.223438	-0.847049	0.7759	0.8154	0.3085	0.000000	0.000000
2459488	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.315962	6.178594	0.146678	4.874441	1.971834	14.830989	45.118575	123.626615	0.7652	0.7894	0.3368	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 104 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 104, Node 8:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 104: 2459608

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Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶